28 February 2000 DriftWeed: a visual metaphor for interactive analysis of multivariate data
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Abstract
We present a visualization technique that allows a user to identify and detect patterns and structures within a multivariate data set. Our research builds on previous efforts to represent multivariate data in a 2D information display through the use of icon plots. Although the icon plot work done by Pickett and Brinstein is similar to our approach, we improve on their efforts in several ways. Our technique allows analysis of a time series without using animation; promotes visual differentiation of information clusters based on measures of variance; and facilitates exploration through direct manipulation of geometry based on scales of variance. Our goal is to provide a visualization that implicitly conveys the degree to which an elements ordered collection of attributes varies from the prevailing pattern of attributes for other elements in the collection. We apply this technique to multivariate abstract data nd use it to locate exceptional elements in a data set and divisions among clusters.
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Stuart J. Rose, Stuart J. Rose, Pak Chung Wong, Pak Chung Wong, } "DriftWeed: a visual metaphor for interactive analysis of multivariate data", Proc. SPIE 3960, Visual Data Exploration and Analysis VII, (28 February 2000); doi: 10.1117/12.378887; https://doi.org/10.1117/12.378887
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